requested changes

Author: aditya520

pages/price-feeds/how-pyth-works/price-aggregation.mdx

@@ -13,7 +13,7 @@ Second, the **aggregate price should appropriately weight data sources with diff
 ![](../../../images/Price_Aggregation_2.png)
 
 Finally, the **aggregate confidence interval should reflect the variation between publishers’ prices.**
-Under normal market conditions, we expect the product to trade at a similar price across exchanges.
+Under normal market conditions, we expect a product to trade at a similar price across exchanges.
 In these cases, we would like the aggregate confidence interval to reflect the confidence intervals of the individual data providers, as shown in the figure on the left.
 However, in some rare situations, a product can trade at different prices on different exchanges.
 In these cases, the aggregate confidence interval should widen out to reflect the variation between these prices, as shown in the figure on the right.
@@ -28,7 +28,7 @@ The second step computes the distance from the aggregate price to the 25th and 7
 
 This process acts like a hybrid between a mean and a median, giving confident publishers more influence, while still capping the maximum influence of any single publisher.
 The algorithm has an interpretation as computing the minimum of an objective function that penalizes the aggregate price from deviating too far from the publishers' prices.
-This interpretation allows us to prove the properties of the algorithm's behavior: for example, the aggregate price will always lie between the 25th and 75th percentiles of the publishers' prices.
+This interpretation allows us to prove properties of the algorithm's behavior: for example, the aggregate price will always lie between the 25th and 75th percentiles of the publishers' prices.
 
 **Scenarios**
 

pages/price-feeds/how-pyth-works/pythnet.mdx

@@ -6,10 +6,9 @@ Pythnet forms the core of Pyth's off-chain price feeds that serve all blockchain
 
 Pythnet is powered by Solana technology: it runs the same validator software but is a Pyth-specific chain that is independent of Solana's mainnet.
 The Pyth Data Association enables each data provider to operate one validator by delegating them the necessary stake.
-Once governance is live, it will take over the management of validators from the Pyth Data Association.
 
 The purpose of Pythnet is to provide a secure and reliable computing substrate for Pyth's price aggregation.
-Recall that Pyth's data providers submit their price measurements for each product.
+Recall that Pyth's data providers submit their own price measurements for each product.
 The Pyth protocol needs to combine these prices to produce a single aggregate price.
 This computation needs to be performed securely -- prices must be combined correctly -- and reliably -- so that accurate and up-to-date price information is always available for applications.
 Pythnet solves both of these problems.

pages/price-feeds/price-feed-ids.mdx

@@ -8,3 +8,9 @@ Price feeds also have different IDs in the Stable and Beta channels.
 
 The full catalog of price feeds is listed on the [pyth.network website](https://pyth.network/price-feeds/).
 The [Price Feed ID reference](https://pyth.network/developers/price-feed-ids) also lets you identify a feed's ID in your chosen ecosystem.
+
+## Solana Price Feed Accounts
+
+On Solana, each feed additionally has a collection of **price feed accounts** containing the feed's data.
+The addresses of these accounts are programmatically derived from the feed id and a shard id, which is simply a 16-bit number.
+See [How to Use Real-Time Data on Solana](price-feeds/use-real-time-data/solana#write-frontend-code) for more information on price feed accounts.