Quantum speed-up in global optimization of binary neural nets

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Parallel Speed-Up of Monte Carlo Methods for Global Optimization

Introduction In this article we will be concerned with the optimization of a scalar-valued function u = f(x), x ∈ D, defined on some set D. Often D is a subset of n-dimensional Euclidean space R. Further we impose the condition that D be a finite set although we do not restrict the size of its cardinality. Thus D might be the set of all n-tuples of computer floating point numbers. In this way o...

متن کامل

Quantum Speed-up of Computations

1. The Physical Church-Turing Thesis. Physicists often interpret the Church-Turing Thesis as saying something about the scope and limitations of physical computing machines. Although this was not the intention of Church or Turing, the Physical Church Turing thesis is interesting in its own right. Consider, for example, Wolfram's formulation: One can expect in fact that universal computers are a...

متن کامل

Speed-up via Quantum Sampling

The Markov Chain Monte Carlo method is at the heart of most fully-polynomial randomized approximation schemes for #P-complete problems such as estimating the permanent or the value of a polytope. It is therefore very natural and important to determine whether quantum computers can speed-up classical mixing processes based on Markov chains. To this end, we present a new quantum algorithm, making...

متن کامل

Origin of the quantum speed-up

Bob chooses a function from a set of functions and gives Alice the black box that computes it. Alice is to find a characteristic of the function through function evaluations. In the quantum case, the number of function evaluations can be smaller than the minimum classically possible. The fundamental reason for this violation of a classical limit is not known. We trace it back to a disambiguatio...

متن کامل

Quantum Speed-up for Approximating Partition Functions

We achieve a quantum speed-up of fully polynomial randomized approximation schemes (FPRAS) for estimating partition functions that combine simulated annealing with the Monte-Carlo Markov Chain method and use non-adaptive cooling schedules. The improvement in time complexity is twofold: a quadratic reduction with respect to the spectral gap of the underlying Markov chains and a quadratic reducti...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: New Journal of Physics

سال: 2021

ISSN: 1367-2630

DOI: 10.1088/1367-2630/abc9ef