arXiv subjects

Y. S. Nam

Publications and source records attributed to Y. S. Nam.

5 recordsLinked to original sources

arXiv2017

Explicit, analytical radio-frequency heating formulas for spherically symmetric nonneutral plasmas in a Paul trap

We present explicit, analytical heating formulas that predict the heating rates of spherical, nonneutral plasmas stored in a Paul trap as a function of cloud size $S$, particle number $N$, and Paul-trap control parameter $q$ in the low-temperature regime close to the cloud $\rightarrow$ crystal phase transition. We find excellent agreement between our analytical heating formulas and detailed, time-dependent molecular-dynamics simulations of the trapped plasmas. We also present the results of our numerical solutions of a temperature-dependent mean-field equation, which are consistent with our numerical simulations and our analytical results. This is the first time that analytical heating formulas are presented that predict heating rates with reasonable accuracy, uniformly for all $S$, $N$, and $q$.

physics.plasm-ph↗

arXiv2017

Symmetry boosts quantum computer performance

Frequently, subroutines in quantum computers have the structure $\mathcal{F}\mathcal{U}\mathcal{F}^{-1}$, where $\mathcal{F}$ is some unitary transform and $\mathcal{U}$ is performing a quantum computation. In this paper we suggest that if, in analogy to spin echoes, $\mathcal{F}$ and $\mathcal{F}^{-1}$ can be implemented symmetrically such that $\mathcal{F}$ and $\mathcal{F}^{-1}$ have the same hardware errors, a symmetry boost in the fidelity of the combined $\mathcal{F}\mathcal{U}\mathcal{F}^{-1}$ quantum operation results. Running the complete gate--by--gate implemented Shor algorithm, we show that the fidelity boost can be as large as a factor 10. Corroborating and extending our numerical results, we present analytical scaling calculations that show that a symmetry boost persists in the practically interesting case of a large number of qubits. Our analytical calculations predict a minimum boost factor of about 3, valid for all qubit numbers, which includes the boost factor 10 observed in our low-qubit-number simulations. While we find and document this symmetry boost here in the case of Shor's algorithm, we suggest that other quantum algorithms might profit from similar symmetry-based performance boosts whenever $\mathcal{F}\mathcal{U}\mathcal{F}^{-1}$ sub-units of the corresponding quantum algorithm can be identified.

quant-ph↗

arXiv2016

Ion Crystal Metamorphoses in a Paul trap

The standard second-order pseudo-oscillator potential used in many analytical investigations of the properties of ions stored in a Paul trap has serious limitations. In this paper we show that ion-crystal configurations exhibited by 2, 3, and 4 simultaneously stored ions in a Paul trap are not predicted by the standard pseudo-oscillator potential, but are all captured qualitatively and quantitatively by an extended pseudopotential derived in this paper. The power of our extended pseudopotential extends in particular to the prediction of the border lines between different crystal configurations (morphologies) in the Paul trap's $a$, $q$ stability diagram. In the three- and four-ion cases, several of the ion-crystal structures predicted by our improved pseudopotential have never been observed experimentally before. We present them here as a challenge for experiments.

physics.atom-ph↗

arXiv2015

Critical exponents for the cloud-crystal phase transition of charged particles in a Paul Trap

It is well known that charged particles stored in a Paul trap, one of the most versatile tools in atomic and molecular physics, may undergo a phase transition from a disordered cloud state to a geometrically well-ordered crystalline state (the Wigner crystal). In this paper we show that the average lifetime $\barτ_m$ of the metastable cloud state preceding the cloud $\rightarrow$ crystal phase transition follows a powerlaw, $\barτ_m \sim (γ-γ_c)^{-β}$, $γ>γ_c$, where $γ_c$ is the critical value of the damping constant $γ$ at which the cloud $\rightarrow$ crystal phase transition occurs. The critical exponent $β$ depends on the trap control parameter $q$, but is independent of the number of particles $N$ stored in the trap and the trap control parameter $a$, which determines the shape (oblate, prolate, or spherical) of the cloud. For $q=0.15,0.20$, and $0.25$, we find $β=1.20\pm 0.03$, $β=1.61\pm 0.09$, and $β=2.38\pm 0.12$, respectively. In addition we find that for given $a$ and $q$, the critical value $γ_c$ of the damping scales approximately like $γ_c=C \ln [ \ln (N)] + D$ as a function of $N$, where $C$ and $D$ are constants. Beyond their relevance for Wigner crystallization of nonneutral plasmas in Paul traps and mini storage rings, we conjecture that our results are also of relevance for the field of crystalline beams.

physics.comp-ph↗

arXiv2013

Scaling laws for Shor's algorithm with a banded quantum Fourier transform

We investigate the performance of a streamlined version of Shor's algorithm in which the quantum Fourier transform is replaced by a banded version that for each qubit retains only coupling to its $b$ nearest neighbors. Defining the performance $P(n,b)$ of the $n$-qubit algorithm for bandwidth $b$ as the ratio of the success rates of Shor's algorithm equipped with the banded and the full bandwidth ($b=n-1$) versions of the quantum Fourier transform, our numerical simulations show that $P(n,b) \approx \exp[-φ_{max}^2 (n,b)/100]$ for $n < n_t(b)$ (non-exponential regime) and $P(n,b) \approx 2^{-ξ_b (n-8)}$ for $n>n_t(b)$ (exponential regime), where $n_{t}(b)$, the location of the transition, is approximately given by $n_{t}(b)\approx b+5.9 + \sqrt{7.7(b+2)-47}$ for $b\gtrsim 8$, $φ_{max} (n,b) = 2π[2^{-b-1} (n-b-2) + 2^{-n}]$, and $ξ_b\approx 1.1 \times 2^{-2b}$. Analytically we obtain $P(n,b) \approx \exp[-φ_{max}^2 (n,b)/64]$ for $n n_t(b)$, where $ξ_{b}^{(a)} \approx \frac{π^2}{12 \ln(2)} \times 2^{-2b} \approx 1.19 \times 2^{-2b}$. Thus, our analytical results predict the $φ_{max}^2$ scaling ($n n_t$) of the data perfectly. In addition, in the large-$n$ regime, the prefactor in $ξ_b^{(a)}$ is close to the results of our numerical simulations and, in the low-$n$ regime, the numerical scaling factor in our analytical result is within a factor 2 of its numerical value. As an example we show that $b=8$ is sufficient for factoring RSA-2048 with a 95% success rate.

quant-ph↗