Siddhartha Das

Siddhartha Dasdas.seed

May 08 2017 04:30 UTC
May 01 2017 02:21 UTC
Apr 04 2017 15:06 UTC
Mar 28 2017 17:24 UTC
Mar 27 2017 02:38 UTC
Mar 24 2017 03:59 UTC
Mar 17 2017 05:59 UTC
Mar 16 2017 05:50 UTC
Mar 13 2017 13:22 UTC

We feel that we have cited and credited previous works appropriately in our paper. To clarify:

1) The LOCC simulation of a channel and the corresponding adaptive reduction can be found worked out in full generality in the 2012 Master's thesis of Muller-Hermes. We have cited the original paper BDSW96 on this topic and pointed to the Master's thesis of Muller-Hermes for details.

2) A precise and general statement and proof that covariant channels are teleportation simulable can be found in [WTB17]. One can also find this result stated on page 36 of the notes of Michael Wolf from 2012: . We will add a citation to Wolf's notes in an eventual revision.

3) Our paper focuses on quantum reading, where we show how to simplify the form of adaptive protocols in this context. The citation to [TW16] appeared only at the very end of our paper, where we indicated that our results can be extended to the bosonic case. If one consults the arXiv, it becomes clear that the bosonic case of adaptive channel discrimination was indeed first considered in [TW16]. In particular,

3a) The post dated Sep 7 2016 did not contain results about bosonic channels.

3b) The post dated Nov 28 2016 was about adaptive channel discrimination for bosonic channels.

3c) The post dated Nov 29 2016 then included results about adaptive channel discrimination of bosonic channels, most of which had already been stated in .

Mar 13 2017 02:00 UTC
Quantum reading refers to the task of reading out classical information stored in a classical memory. In any such protocol, the transmitter and receiver are in the same physical location, and the goal of such a protocol is to use these devices, coupled with a quantum strategy, to read out as much information as possible from a classical memory, such as a CD or DVD. In this context, a memory cell is a collection of quantum channels that can be used to encode a classical message in a memory. The maximum rate at which information can be read out from a given memory encoded with a memory cell is called the quantum reading capacity of the memory cell. As a consequence of the physical setup of quantum reading, the most natural and general definition for quantum reading capacity should allow for an adaptive operation after each call to the channel, and this is how we define quantum reading capacity in this paper. In general, an adaptive strategy can give a significant advantage over a non-adaptive strategy in the context of quantum channel discrimination, and this is relevant for quantum reading, due to its close connection with channel discrimination. In this paper, we provide a general definition of quantum reading capacity, and we establish several upper bounds on the quantum reading capacity of a memory cell. We also introduce an environment-parametrized memory cell, and we deliver second-order and strong converse bounds for its quantum reading capacity. We calculate the quantum reading capacities for some exemplary memory cells, including a thermal memory cell, a qudit erasure memory cell, and a qudit depolarizing memory cell. We finally provide an explicit example to illustrate the advantage of using an adaptive strategy in the context of zero-error quantum reading capacity.
Mar 12 2017 16:14 UTC
Mar 09 2017 03:14 UTC
Siddhartha Das scited Conditional quantum one-time pad
Mar 08 2017 03:22 UTC
Siddhartha Das scited Information Loss
Feb 22 2017 15:21 UTC
Siddhartha Das scited Locality from the Spectrum
Feb 17 2017 02:00 UTC
Recently, there has been focus on determining the conditions under which the data processing inequality for quantum relative entropy is satisfied with approximate equality. The solution of the exact equality case is due to Petz, who showed that the quantum relative entropy between two quantum states stays the same after the action of a quantum channel if and only if there is a \textitreversal channel that recovers the original states after the channel acts. Furthermore, this reversal channel can be constructed explicitly and is now called the \textitPetz recovery map. Recent developments have shown that a variation of the Petz recovery map works well for recovery in the case of approximate equality of the data processing inequality. Our main contribution here is a proof that bosonic Gaussian states and channels possess a particular closure property, namely, that the Petz recovery map associated to a bosonic Gaussian state $\sigma$ and a bosonic Gaussian channel $\mathcal{N}$ is itself a bosonic Gaussian channel. We furthermore give an explicit construction of the Petz recovery map in this case, in terms of the mean vector and covariance matrix of the state $\sigma$ and the Gaussian specification of the channel $\mathcal{N}$.