Optimization and benchmarking of the thermal cycling algorithm.

Optimization plays a significant role in many areas of science and technology. Most of the industrial optimization problems have inordinately complex structures that render finding their global minima a daunting task. Therefore, designing heuristics that can efficiently solve such problems is of utmost importance.

Quantum supremacy using a programmable superconducting processor.

The promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Here we report the use of a processor with programmable superconducting qubits to create quantum states on 53 qubits, corresponding to a computational state-space of dimension 2 (about 10).

Feeding the multitude: A polynomial-time algorithm to improve sampling.

A wide variety of optimization techniques, both exact and heuristic, tend to be biased samplers. This means that when attempting to find multiple uncorrelated solutions of a degenerate Boolean optimization problem a subset of the solution space tends to be favored while, in the worst case, some solutions can never be accessed by the algorithm used. Here we present a simple postprocessing technique that improves sampling for any optimization approach, either quantum or classical.

Gas Separation through Bilayer Silica, the Thinnest Possible Silica Membrane.

Membrane-based gas separation processes can address key challenges in energy and environment, but for many applications the permeance and selectivity of bulk membranes is insufficient for economical use. Theory and experiment indicate that permeance and selectivity can be increased by using two-dimensional materials with subnanometer pores as membranes. Motivated by experiments showing selective permeation of H/CO mixtures through amorphous silica bilayers, here we perform a theoretical study of gas separation through silica bilayers.

Patch-planting spin-glass solution for benchmarking.

We introduce an algorithm to generate (not solve) spin-glass instances with planted solutions of arbitrary size and structure. First, a set of small problem patches with open boundaries is solved either exactly or with a heuristic, and then the individual patches are stitched together to create a large problem with a known planted solution. Because in these problems frustration is typically smaller than in random problems, we first assess the typical computational complexity of the individual patches using population annealing Monte Carlo, and introduce an approach that allows one to fine-tune the typical computational complexity of the patch-planted system.

Exponentially Biased Ground-State Sampling of Quantum Annealing Machines with Transverse-Field Driving Hamiltonians.

We study the performance of the D-Wave 2X quantum annealing machine on systems with well-controlled ground-state degeneracy. While obtaining the ground state of a spin-glass benchmark instance represents a difficult task, the gold standard for any optimization algorithm or machine is to sample all solutions that minimize the Hamiltonian with more or less equal probability. Our results show that while naive transverse-field quantum annealing on the D-Wave 2X device can find the ground-state energy of the problems, it is not well suited in identifying all degenerate ground-state configurations associated with a particular instance.

Soft bounds on diffusion produce skewed distributions and Gompertz growth.

Constraints can affect dramatically the behavior of diffusion processes. Recently, we analyzed a natural and a technological system and reported that they perform diffusion-like discrete steps displaying a peculiar constraint, whereby the increments of the diffusing variable are subject to configuration-dependent bounds. This work explores theoretically some of the revealing landmarks of such phenomenology, termed "soft bound.

Helium isotope enrichment by resonant tunneling through nanoporous graphene bilayers.

Graphene is impermeable to gases, but introducing subnanometer pores can allow for selective gas separation. Because graphene is only one atom thick, tunneling can play an important role, especially for low-mass gases such as helium, and this has been proposed as a means of separating (3)He from (4)He. In this paper, we consider the possibility of utilizing resonant tunneling of helium isotopes through nanoporous graphene bilayers.

Evidence for soft bounds in Ubuntu package sizes and mammalian body masses.

The development of a complex system depends on the self-coordinated action of a large number of agents, often determining unexpected global behavior. The case of software evolution has great practical importance: knowledge of what is to be considered atypical can guide developers in recognizing and reacting to abnormal behavior. Although the initial framework of a theory of software exists, the current theoretical achievements do not fully capture existing quantitative data or predict future trends.

Coevolution of Glauber-like Ising dynamics and topology.

We study the coevolution of a generalized Glauber dynamics for Ising spins with tunable threshold and of the graph topology where the dynamics takes place. This simple coevolution dynamics generates a rich phase diagram in the space of the two parameters of the model, the threshold and the rewiring probability. The diagram displays phase transitions of different types: spin ordering, percolation, and connectedness.