25,505 research outputs found
Redundant Logic Insertion and Fault Tolerance Improvement in Combinational Circuits
This paper presents a novel method to identify and insert redundant logic
into a combinational circuit to improve its fault tolerance without having to
replicate the entire circuit as is the case with conventional redundancy
techniques. In this context, it is discussed how to estimate the fault masking
capability of a combinational circuit using the truth-cum-fault enumeration
table, and then it is shown how to identify the logic that can introduced to
add redundancy into the original circuit without affecting its native
functionality and with the aim of improving its fault tolerance though this
would involve some trade-off in the design metrics. However, care should be
taken while introducing redundant logic since redundant logic insertion may
give rise to new internal nodes and faults on those may impact the fault
tolerance of the resulting circuit. The combinational circuit that is
considered and its redundant counterparts are all implemented in semi-custom
design style using a 32/28nm CMOS digital cell library and their respective
design metrics and fault tolerances are compared
Faster quantum mixing for slowly evolving sequences of Markov chains
Markov chain methods are remarkably successful in computational physics,
machine learning, and combinatorial optimization. The cost of such methods
often reduces to the mixing time, i.e., the time required to reach the steady
state of the Markov chain, which scales as , the inverse of the
spectral gap. It has long been conjectured that quantum computers offer nearly
generic quadratic improvements for mixing problems. However, except in special
cases, quantum algorithms achieve a run-time of , which introduces a costly dependence on the Markov chain size
not present in the classical case. Here, we re-address the problem of mixing of
Markov chains when these form a slowly evolving sequence. This setting is akin
to the simulated annealing setting and is commonly encountered in physics,
material sciences and machine learning. We provide a quantum memory-efficient
algorithm with a run-time of ,
neglecting logarithmic terms, which is an important improvement for large state
spaces. Moreover, our algorithms output quantum encodings of distributions,
which has advantages over classical outputs. Finally, we discuss the run-time
bounds of mixing algorithms and show that, under certain assumptions, our
algorithms are optimal.Comment: 20 pages, 2 figure
Quantum Programming Made Easy
We present IQu, namely a quantum programming language that extends Reynold's
Idealized Algol, the paradigmatic core of Algol-like languages. IQu combines
imperative programming with high-order features, mediated by a simple type
theory. IQu mildly merges its quantum features with the classical programming
style that we can experiment through Idealized Algol, the aim being to ease a
transition towards the quantum programming world. The proposed extension is
done along two main directions. First, IQu makes the access to quantum
co-processors by means of quantum stores. Second, IQu includes some support for
the direct manipulation of quantum circuits, in accordance with recent trends
in the development of quantum programming languages. Finally, we show that IQu
is quite effective in expressing well-known quantum algorithms.Comment: In Proceedings Linearity-TLLA 2018, arXiv:1904.0615
On-line diagnosis of unrestricted faults
A formal model for the study of on-line diagnosis is introduced and used to investigate the diagnosis of unrestricted faults. A fault of a system S is considered to be a transformation of S into another system S' at some time tau. The resulting faulty system is taken to be the system which looks like S up to time tau, and like S' thereafter. Notions of fault tolerance error are defined in terms of the resulting system being able to mimic some desired behavior as specified by a system similar to S. A notion of on-line diagnosis is formulated which involves an external detector and a maximum time delay within which every error caused by a fault in a prescribed set must be detected. It is shown that if a system is on-line diagnosable for the unrestricted set of faults then the detector is at least as complex, in terms of state set size, as the specification. The use of inverse systems for the diagnosis of unrestricted faults is considered. A partial characterization of those inverses which can be used for unrestricted fault diagnosis is obtained
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